A Spatiotemporal Deep Learning Approach for Urban Pluvial Flood Forecasting with Multi-Source Data

A Spatiotemporal Deep Learning Approach for Urban Pluvial Flood Forecasting with Multi-Source Data

This study presents a deep-learning-based forecast model for spatial and temporal prediction of pluvial flooding. The developed model can produce the flooding situation for the upcoming time steps as a sequence of flooding maps. Thus, a dynamic overview of the forthcoming flooding situation is gener...

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Bibliographic Details
Main Authors: Benjamin Burrichter, Julian Hofmann, Juliana Koltermann da Silva, Andre Niemann, Markus Quirmbach
Format: Article
Language:English
Published: MDPI AG 2023-05-01
Series:Water
Subjects:
urban pluvial flooding
deep learning
spatiotemporal modeling
real-time flood forecasting
Online Access:https://www.mdpi.com/2073-4441/15/9/1760

Internet

https://www.mdpi.com/2073-4441/15/9/1760

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